Finite horizon robust model predictive control with terminal cost constraints

Author(s): D. Chu ; T. Chen ; H.J. Marquez
DOI: 10.1049/ip-cta:20045112

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Author(s): D. Chu ¹ ; T. Chen ¹ ; H.J. Marquez ¹
- Affiliations: 1: Department of Electrical and Computer Engineering, University of Alberta, Canada
Source: Volume 153, Issue 2, March 2006, p. 156 – 166
DOI: 10.1049/ip-cta:20045112 , Print ISSN 1350-2379, Online ISSN 1359-7035

A finite horizon model predictive control (MPC) algorithm that is robust to modelling uncertainties is developed along with the construction of a moving average system matrix to capture modelling uncertainties and facilitate the future output prediction. The authors' main focus is on the step tracking problem. Using linear matrix inequality techniques, the design is converted into a semi-definite optimisation problem. Closed-loop stability, known to be one of the most challenging topics in finite horizon MPC, is treated by adding extra terminal cost constraints in the semi-definite optimisation. A simulation example demonstrates that the approach can be useful for practical applications.

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Finite horizon robust model predictive control with terminal cost constraints

Finite horizon robust model predictive control with terminal cost constraints

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